Communications for Statistical Applications and Methods

The Korean Statistical Society (한국통계학회)
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Change point analysis in Bitcoin return series : a robust approach

  • Song, Junmo (Department of Statistics, Kyungpook National University) ;
  • Kang, Jiwon (Department of Computer Science and Statistics, Jeju National University)
  • Received : 2021.04.09
  • Accepted : 2021.05.21
  • Published : 2021.09.30
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Abstract

Over the last decade, Bitcoin has attracted a great deal of public interest and Bitcoin market has grown rapidly. One of the main characteristics of the market is that it often undergoes some events or incidents that cause outlying observations. To obtain reliable results in the statistical analysis of Bitcoin data, these outlying observations need to be carefully treated. In this study, we are interested in change point analysis for Bitcoin return series having such outlying observations. Since these outlying observations can affect change point analysis undesirably, we use a robust test for parameter change to locate change points. We report some significant change points that are not detected by the existing tests and demonstrate that the model allowing for parameter changes is better fitted to the data. Finally, we show that the model with parameter change can improve the forecasting performance of Value-at-Risk.

Keywords

Acknowledgement

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2019R1I1A3A01056924) (J. Song) and by the 2020 scientific promotion program funded by Jeju National University (J. Kang).

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